Nvidia announces AMR platform for AI-driven logistics

LinkedIn +

US technology company Nvidia has announced the introduction of its Isaac autonomous mobile robot (AMR) platform for the logistics industry.

Designed to enhance the development of AI-driven logistics by providing a complete path to build industrial and human-robot simulations as well as route optimisations, the Isaac AMR platform extends Nvidia’s capabilities for building and deploying robotics applications, bringing mapping, site analytics and fleet optimisation onto Nvidia EGX servers.

The Isaac AMR framework is available on the Nvidia NGC software hub and within the Nvidia Omniverse platform to create digital twins of a facility where AMRs will be deployed.

Nvidia Isaac Sim, built on Omniverse, simulates the behaviour of robot fleets, people and other machines in the digital twins with high-fidelity physics and perception, and enables synthetic data generation for training of AI models.

Isaac AMR consists of GPU-accelerated AI technologies and SDKs including DeepMap, ReOpt and Metropolis – technologies orchestrated and cloud delivered with Nvidia Fleet Command.

According to Nvidia, AMR deployments can access DeepMap’s cloud-based SDK to help accelerate robot mapping of large facilities from weeks to days, while achieving centimetre-level accuracy.

Isaac AMR is the result of years of research and product development at Nvidia

Additionally, the DeepMap Update Client enables robot maps to be updated as frequently as necessary, in real time, while the DeepMap SDK delivers layers of intelligence to maps by adding semantic understanding – so robots can identify the objects and know if they can move one way or not. It’s also capable of addressing both indoor and outdoor map building.

Furthermore, the Nvidia Metropolis video analytics platform has been developed to meet the need for higher level real-time ‘outside-in’ perception by providing access to cameras and sensors deployed throughout a factory or warehouse floor.

And with Metropolis, AMRs have access to additional layers of situational awareness on the factory floor, enabling them to avoid high-congestion areas, eliminating blind spots and enhanced visibility of both people and other AMRs. Also, Metropolis’s pre-trained models provide options for customising site-specific needs.

Finally, Nvidia ReOpt AI software libraries can be used to optimise vehicle route planning and logistics in real time, which can be applied to AMR fleets. Using Isaac Sim, companies can simulate multiple AMR interactions with Nvidia ReOpt in digital twins. According to Nvidia, these can be implemented before deploying robots in production as situations change.

Nvidia ReOpt also provides dynamic reoptimisation of routes to a fleet of heterogeneous AMRs based on a number of constraints.

Share this story: